Confluent

Native Flink functions for anomaly detection, fraud prevention, forecasting, sentiment analysis, and other machine learning capabilities executed directly within data streams.

Feature enabling real-time mirroring and replication of Kafka topics and metadata across clusters, supporting zero-downtime migrations and disaster recovery.

MCP Server and Agent Skills tools that enable developers to build AI agents with access to real-time streaming data and data governance capabilities.

Developer tools including MCP Server and Agent Skills for building AI applications on top of Confluent's data streaming platform.

Cloud-native data streaming platform powered by Kora engine, providing autoscaling, enterprise-grade performance, and 99.99% uptime SLA for production workloads.

A fully managed service on Confluent Cloud for building real-time, replayable, context-rich AI systems powered by Apache Kafka and Flink. Combines historical evaluation, continuous processing, and real-time serving for production AI applications.

Self-managed, cloud-native distribution of Apache Kafka with built-in governance, security, and operational tools for on-premises and private cloud deployments.

Converts any Kafka topic into a stream of vector embeddings to continuously supply up-to-date context for RAG and semantic search applications.

Cloud-native engine powering Confluent Cloud with autoscaling capabilities and 20-90%+ throughput savings compared to traditional Kafka deployments.

Transforms features into representations more suitable for downstream processors within streaming pipelines.

Provides secure and scalable integration with any model, tool, or data system via MCP for serving real-time context to AI applications.

Identifies unexpected deviations in real time using multivariate analysis to improve data quality and enable faster decision-making in streaming data.

A fully managed service that delivers trustworthy, structured, real-time context to any AI app or agent via the Model Context Protocol (MCP). Serves live, governed data from enriched enterprise sources at low latency.

Performs real-time analysis and forecasting on streaming data without requiring in-depth data science expertise. Enables actionable insights from live data streams.

Invokes remote AI/ML models directly within Flink, providing a unified platform for both data processing and AI/ML tasks without separate infrastructure.

Fully managed governance suite including Schema Registry for managing data formats (Avro, Protobuf, JSON Schema) and ensuring data quality across streaming pipelines.

A framework for building, testing, and deploying event-driven AI agents that run natively on Kafka and Flink. Agents have access to real-time contextualized data to monitor events and take instant, informed action.

Converts Kafka topics to tables in a few clicks, simplifying data access and making streaming data more accessible.

Updated Confluent Cloud platform with enhanced accessibility for Flink and Kafka for AI-ready streaming, designed to make data and pipelines more accessible for AI workflows.